MIMO wireless communication system and wireless communication apparatuses

ABSTRACT

A MIMO wireless communication system and wireless communication apparatuses are disclosed that increase the practically usable communication channel capacity in the Shannon channel capacity that determines the ratio of maximum signal transmission speed to frequency. Each wireless communication apparatus includes antenna units that transmit and receive radio frequency signals, and a weight controlling unit that provides weights with respect to the antenna units. The antenna units are formed by adaptive array antenna units that can change the directivity by varying weights with respect to antenna elements. The weight controlling unit includes an eigenvalue calculating unit that calculates the eigenvalues of a matrix HH* (H being a channel matrix), an inverse calculation unit that calculates such a channel matrix H′ as to have all eigenvalues within a predetermined range that includes the average value of the calculated eigenvalues, and a directivity adjusting unit that adjusts the adaptive array antenna directivity so that the current channel matrix H approaches the calculated channel matrix H′.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.10/901,426 filed on Mar. 16, 2004, pending, and claims priority fromJapanese Patent Application Number 2003-200446 filed Jul. 23, 2003, thecontents of which are hereby incorporated by reference.

BACKGROUND OF THE INVENTION

The present invention relates to a multiple-input-multiple-output (MIMO)wireless communication system and wireless communication apparatusesthat are used in the MIMO wireless communication system.

In this field of technology, intensive studies are being made onwireless interfaces to improve communication capacities, communicationspeed, communication quality, resource utilizing rates, and the like.Particularly, in MIMO systems that have been attracting public attentionrecently, two or more antennas are provided at both the transmission endand the reception end, so that a multiple-input-multiple-output systemis formed with wireless transmission channels. With a larger number ofantennas for transmission and reception, the usability of space isincreased, and the transmission capacity can also be increased.

FIG. 1 is a conceptual view of a MIMO communication system. For ease ofexplanation, the left side in FIG. 1 is the transmission end, and theright side is the reception end, though each end normally has bothtransmitting and receiving functions. A transmission signal vectorx(t)=(x₁(t), x₂(t), . . . , x_(M)(t))^(T) is transmitted through each ofM antennas at the transmission end. Here, T represents “transpose”, andM is an integer of 2 or greater. It is possible to add an adjustableweight μj to each of the M antennas. Here, j is an integer between 1 andM. Likewise, N antennas are provided at the reception end. Based on thesignal received at each antenna, a reception signal vector y(t)=(y₁(t),y₂(t), . . . , y_(N)(t)) is obtained. Here, N is an integer of 2 orgreater, and may be either the same as M or different from M. It is alsopossible to add an adjustable weight v_(i) to each of the N antennas atthe reception end. Here, i is an integer between 1 and N.

In this case, the relationship between the transmission vector x(t) andthe reception vector y(t) is expressed by the following equation:$\begin{matrix}{{y(t)} = {{\sqrt{\frac{\rho}{M}}{{Hx}(t)}} + {n(t)}}} & (1)\end{matrix}$

where H is a channel matrix that represents the transmissioncharacteristics of the wireless transmission channels among theantennas, and the matrix elements h_(ij) represent the transmissioncharacteristics (in a baseband representation) of the wirelesstransmission channel between the jth antenna of the transmission end andthe ith antenna of the reception end. Here, i is an integer between 1and N, and j is an integer between 1 and M. Accordingly, the channelmatrix H is a matrix having N rows and M columns (N by M). Further, ρrepresents the transmission power, and n(t) represents the noise vectorthat is introduced in the wireless transmission channels and is assumedto be expressed by an additive Gaussian noise vector. The noisecomponents at any time can be evaluated from random numbers inaccordance with a Gaussian distribution.

If knowledge of the channel matrix H is acquired by the reception end,the communication channel capacity (or the Shannon capacity) expressedas a ratio of (maximum) signal transmission speed to frequency (bps/Hz)can be evaluated by the following expression (2) with the expected valueof the amount I of conditional mutual information as to the transmissionvector x(t) and the reception vector y(t). $\begin{matrix}{E\left\lbrack {{I\left( {x;{y\left. H \right)}} \right\rbrack} \leq {E\left\lbrack {\log\quad{\det\left( {I_{N} + {\frac{\rho}{M}{HH}^{*}}} \right)}} \right\rbrack}} \right.} & (2)\end{matrix}$

where: H represents the ergodicity obtained by evaluating the ensemblemean value using the time mean value; E [·] indicates that the term isthe expected value; I_(N) represents the unit matrix having a dimensionN; [*] indicates that the term is a transposed conjugate; and det (·)represents a determinant of the matrix.

Further, if the knowledge of the channel matrix H is shared between thereception end and the transmission end, the communication channelcapacity C can be expressed by the following equation (3):$\begin{matrix}{C = {\sum\limits_{i = 1}^{\alpha}{\log_{2}\left\lbrack {1 + {\frac{\rho}{M}\lambda_{i}}} \right\rbrack}}} & (3)\end{matrix}$

where α and λ_(i) represent the number of ranks of the matrix expressedby HH* and the ith eigenvalue, respectively. Here, i is an integerbetween 1 and α.

MIMO wireless communication systems and the communication channelcapacities are disclosed in the following Non-Patent Documents 1 through4. (Non-Patent Document 1)

I. E. Telatar, “Capacity of Multi-Antenna Gaussian Channels”, Bell Labs.Technical Memorandum, 1995 (See also “Europ. Trans. Telecommun.”), Vol.10, No. 6, pp. 585-595, November-December 1999) (Non-Patent Document 2)

G. J. Foschini and M. Gans, “On the Limits of Wireless Communication ina Fading Environment When Using Multiple Antennas”, Wireless PersonalCommun., Vol. 6, No. 3, pp. 311-335, March 1998 (Non-Patent Document 3)

G. J. Foschini, “Layered Space-Time Architecture for WirelessCommunication in a Fading Environment When Using Multiple Antennas”,Bell Syst. Tech. J., Vol. 1, No. 2, pp. 41-59, 1996 (Non-Patent Document4)

J. B. Andersen, “Array Gain and Capacity for Known Random Channels withMultiple Element Arrays at Both Ends”, IEEE J. Sel. Areas in Commun.,Vol. 18, No. 11, pp. 2172-2178, November 2000

In accordance with equation (3), the entire communication channelcapacity C can be determined by the sum of the channel capacities C_(i)of communication channels that correspond to the eigenvalues λ_(i) ofthe matrix HH*. In that case, as the communication channel capacitiesC_(i) are proportional to the eigenvalues λ_(i), the channel capacity ofa communication channel corresponding to a small eigenvalue is small,and such a communication channel has a poor throughput and a high biterror rate. Accordingly, with a very small eigenvalue, it is difficultto use the channel capacity of the communication channel correspondingto the eigenvalue in actual wireless communications, and only a part ofthe entire communication channel capacity C can be used.

SUMMARY OF THE INVENTION

A general object of the present invention is to provide MIMO wirelesscommunication systems and MIMO wireless communication apparatuses inwhich the above disadvantages are eliminated.

A more specific object of the present invention is to provide a MIMOwireless communication system that increases practical communicationchannel capacities among the Shannon channel capacities that determinethe ratio of maximum signal transmission speed to frequency, andwireless communication apparatuses that are employed in the MIMOwireless communication system.

The above objects of the present invention are achieved by a wirelesscommunication apparatus that is employed in amultiple-input-multiple-output wireless communication system, andincludes: a plurality of antenna units that transmit or receive radiofrequency signals; and a weight controlling unit that gives a weightwith respect to each of the antenna units.

In this wireless communication apparatus, at least one of the antennaunits is formed by an adaptive array antenna unit that has a pluralityof antenna elements, and directivity can be changed by varying theweights with respect to the antenna elements.

The weight controlling unit includes:

an eigenvalue calculating unit that calculates the eigenvalues of amatrix represented by the product of a current channel matrixrepresenting the transmission characteristics of the wirelesstransmission channels of the respective antenna units and a conjugatetransposed matrix of the current channel matrix;

an inverse calculation unit that calculates such a channel matrix as tohave all eigenvalues within a predetermined range that includes theaverage value of the calculated eigenvalues but does not include thesmallest one of the calculated eigenvalues; and

a directivity adjusting unit that adjusts the directivity of theadaptive array antenna unit, so that the current channel matrixapproaches to the channel matrix calculated by the inverse calculationunit.

The above and other objects and features of the present invention willbecome more apparent from the following description taken in conjunctionwith the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram of a MIMO communication system;

FIG. 2 is a graph of the results of a simulation test conducted toexamine the cumulative distributions of eigenvalues in a case of M=N=2;

FIG. 3 is a graph of the results of a simulation test conducted toexamine the cumulative distributions of eigenvalues in a case of M=N=4;

FIG. 4 is a graph of the results of a simulation test conducted toexamine the cumulative distributions of communication channel capacitiesin a case of M=N=2;

FIG. 5 is a graph of the results of a simulation test conducted toexamine the cumulative distributions of communication channel capacitiesin a case of M=N=4;

FIG. 6 is a graph of the results of a simulation test conducted toexamine the bit error rates with respect to communication channelcapacities in a case of M=N=2;

FIG. 7 is a graph of the results of a simulation test conducted toexamine the bit error rates with respect to communication channelcapacities in a case of M=N=4;

FIG. 8 is a schematic diagram illustrating wireless communicationapparatuses that are employed in a MIMO wireless communication system inaccordance with the present invention;

FIG. 9 is a functional block diagram of each of the weight controllingunits of the wireless communication apparatuses shown in FIG. 8;

FIG. 10 is a schematic diagram illustrating an adaptive array antennathat can be employed as an antenna unit of the wireless communicationapparatuses shown in FIG. 8;

FIG. 11 is a schematic diagram illustrating another adaptive arrayantenna that can be employed as an antenna unit of the wirelesscommunication apparatuses shown in FIG. 8; and

FIG. 12 is a schematic diagram illustrating yet another adaptive arrayantenna that can be employed as an antenna unit of the wirelesscommunication apparatuses shown in FIG. 8.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following, the principles of the present invention are described,with reference to the results of various simulation tests.

FIG. 2 shows the results of a simulation test conducted to examine thevariation of the eigenvalues of a matrix HH*. In FIG. 2, the ordinateaxis indicates the cumulative distribution, and the abscissa axisindicates the sizes of the eigenvalues. In this simulation test, thefollowing conditions and procedures were employed.

1) The matrix elements h_(ij) of a channel matrix H are determined bygenerating random numbers in accordance with a complex Gaussiandistribution having an average value of 0 and a standard deviation of 1(CN (0, 1)).

2) Based on the determined channel matrix H, eigenvalues λ₁ and λ₂ ofHH* are determined. Since M and N are both 2, HH* is a 2 by 2 matrix. Ifthe number of ranks is 2, the two eigenvalues λ₁ and λ₂ (λ₁ □ λ₂) areobtained.

3) The procedures 1) and 2) are repeated many times, so as to obtain anumber of eigenvalues λ₁ ^((j)) and λ₂ ^((j)) (j representing the numberof the repeating times).

4) A curve MIMOch1 is obtained by examining the distribution and thecumulative distribution of the larger eigenvalue λ₁, and a curve MIMOch2is obtained by examining the distribution and the cumulativedistribution of the smaller eigenvalue λ₂. Further, a curveMIMO_(average) is obtained by examining the distribution of and thecumulative distribution of the average value λ_(ave) of the eigenvaluesλ₁ and λ₂, and a curve MIMO_(total) is obtained by examining thedistribution and the cumulative distribution of the total valueλ_(total) of the eigenvalues λ₁ and λ₂. For comparison purposes, a curveSISO that represents values (h₁₁ ²) obtained with asingle-input-single-output (SISO) wireless communication system is alsoshown.

In FIG. 2, the curve MIMOch2 that represents the cumulative distributionof the smaller eigenvalue λ₂ is located on the left side, and the curveMIMOch1 that represents the cumulative distribution of the largereigenvalue λ₁ is located on the right side in accordance with therelationship between the eigenvalues. As for the smaller eigenvalue λ₂,90 percent of the distribution is 0 dB or below. As for the largereigenvalue λ₁, on the other hand, only several percent of thedistribution is 0 dB or below.

FIG. 3 shows the results of a simulation test that is different from thesimulation test of FIG. 2 in that both M and N are 4. More specifically,the distributions and the cumulative distributions of four eigenvaluesλ₁, λ₂, λ₃, and λ₄ (λ₁ □ λ₂ □ λ₃ □ λ₄) are examined to obtain curvesMIMOch1 through MIMOch4. Further, the distributions and the cumulativedistributions of the average value of the eigenvalues and the totalvalue of the eigenvalues are examined to obtain a curve MIMO_(average)and a curve MIMO_(total). For comparison purposes, a curve obtained witha SISO system is also shown. As can be seen from FIG. 3, the cumulativedistribution curves are arranged in accordance with the relationshipamong the eigenvalues λ₁, λ₂, λ₃, and λ₄.

FIG. 4 shows the results of a simulation test that was conducted byexamining the cumulative distribution of communication channelcapacities based on the eigenvalues obtained through the aboveprocedures 1) through 3). In this simulation test, the signal-to-noiseratio (SNR) is assumed to be 18 dB. A curve MIMOch1 is obtained byexamining the distribution and the cumulative distribution of thecommunication channel capacity based on the larger eigenvalue λ₁, and acurve MIMOch2 is obtained by examining the distribution and thecumulative distribution of the communication channel capacity based onthe smaller eigenvalue λ₂. A curve MIMO_(average) is obtained byexamining the distribution and the cumulative distribution of thecommunication channel capacity based on the average value λ_(ave) of theeigenvalues λ₁ and λ₂, and a curve MIMO_(total) is obtained by examiningthe distribution and the cumulative distribution of the communicationchannel capacity with respect to the total value λ_(total) of theeigenvalues λ₁ and λ₂. Also, a curve MIMO_(average total) is obtained bydoubling the channel capacity based on the average value λ_(ave).Further, a curve SISO that represents the communication channel capacityof a signal-input-single-output (SISO) wireless communication system isalso shown for comparison purposes.

As described above, the eigenvalues are proportional to thecommunication channel capacities. Accordingly, the curve MIMOch2 thatrepresents the communication channel capacity calculated from thesmaller eigenvalue λ₂ is shown on the left side, and the curve MIMOch1that represents the communication channel capacity based on the largereigenvalue λ₁ is shown on the right side, which are the same as thesimulation results shown in FIG. 2. More specifically, as for thesmaller eigenvalue λ₂, about 90 percent of the channel capacitydistribution is 5 bps/Hz or below. As for the larger eigenvalue λ₁, onthe other hand, only several percent of the channel capacitydistribution is 5 bps/Hz or below. Further, the communication channelcapacity with respect to the smaller eigenvalue λ₂ is smaller than thatof the SISO system. Also, the total communication channel capacityMIMO_(average total) based on the average value λ_(ave) provides alarger communication channel capacity than the total communicationchannel capacity MIMO_(total) based on the eigenvalues λ_(i).

FIG. 5 shows the results of a simulation test that is different from thesimulation test of FIG. 4 in that both M and N are 4. More specifically,the distributions and the cumulative distributions of communicationchannel capacities based on four eigenvalues λ₁, λ₂, λ₃, and λ₄ (λ₁ □ λ₂□ λ₃ □ λ₄) are examined to obtain curves MIMOch1 through MIMOch4.Further, the distributions and the cumulative distributions ofcommunication channel capacities based on the average value of theeigenvalues and the total value of the eigenvalues are examined toobtain a curve MIMO_(average) and a curve MIMO_(total), respectively.Also, a curve MIMO_(average total) is obtained by quadrupling thecommunication channel capacity based on the average value λ_(ave). Forcomparison purposes, a curve obtained in a case of a SISO system is alsoshown. As can be seen from FIG. 5, the cumulative distribution curvesare arranged in accordance with the relationship among the eigenvaluesλ₁, λ₂, λ₃, and λ₄.

FIG. 6 shows the results of a simulation test that was conducted on thebit error rates (BER) obtained when BPSK-modulated signals weretransmitted through the communication channels corresponding to theeigenvalues of a matrix HH*. In this test, the values M and N are both2. A curve MIMOch2 is obtained by examining the bit error rate in thecommunication channel with respect to the smaller eigenvalue λ₂, and acurve MIMOch1 is obtained by examining the bit error rate in thecommunication channel with respect to the larger eigenvalue λ₁. A curveMIMO_(ave) and a curve MIMO_(total) are obtained by examining the biterror rates in the communication channels with respect to the averagevalue and the total value of the eigenvalues. Also, a curveMIMO_(average total) is obtained by examining the bit error rate withthe total communication channel capacity based on the average valueλ_(ave). Further, a curve that is obtained in a case of a SISO system isalso shown for comparison purposes.

As can be seen from FIG. 6, the bit error rate in the communicationchannel with respect to the larger eigenvalue λ₁ is low, and the biterror rate in the communication path with respect to the eigenvalue λ₂is high. In other words, the larger eigenvalue λ₁ provides a desirablecommunication channel, but the smaller eigenvalue λ₂ does not provide adesirable communication channel. In a case where Eb/N_(o) is 10 dB, forexample, the bit error rate (MIMOch1) in the communication channel withrespect to the larger eigenvalue is approximately 10⁻⁵, but the biterror rate (MIMOch2) in the communication channel with respect to thesmaller eigenvalue is higher than 10⁻².

FIG. 7 also shows the results of a simulation test that was conducted onthe bit error rates (BER) obtained when BPSK-modulated signals weretransmitted through the communication channels corresponding to theeigenvalues of a matrix HH*. In this test, the values M and N are bothassumed to be 4. The bit error rates in the communication channels withrespect to four eigenvalues λ₁, λ₂, λ₃, and λ₄ (λ₁ □ λ₂ ∇ λ₃ □ λ₄) areexamined to obtain curves MIMOch1 through MIMOch4. The bit error ratesin the communication channels with respect to the average value of theeigenvalues and the total value of the eigenvalues are examined toobtain a curve MIMO_(average) and a curve MIMO_(total). Also, a curveMIMO_(average total) is obtained by examining the bit error rate withthe total communication channel capacity based on the average valueλ_(ave). Further, a curve obtained in a case of a SISO system is shownfor comparison purposes.

As can be seen from FIG. 7, the bit error rate curves are arranged inaccordance with the relationship among the eigenvalues λ₁, λ₂, λ₃, andλ₄. Accordingly, a larger eigenvalue provides a desirable communicationchannel, but a smaller eigenvalue does not provide a desirablecommunication channel. Especially, the bit error rate in thecommunication channel with respect to the smallest eigenvalue λ₄ ishigher than the bit error rate in the case of a SISO system.

As described above, the communication channel capacities and the biterror rates calculated based on eigenvalues and the cumulativedistributions of the eigenvalues reveal that a communication channelwith respect to a small eigenvalue cannot be a better communicationchannel than that of a SISO system in terms of the throughput and biterror rate. As a result, the entire communication channel capacityC_(all) might decrease. In a case where the communication channelcapacity with respect to the larger eigenvalue λ₁ is represented byC_(large), and the communication channel capacity with respect to thesmaller eigenvalue λ₂ is represented by C_(small), with M and N being 2,the entire communication channel capacity C_(all) is expressed by:C_(all)=C_(large)+C_(small)

If the communication channel capacity C_(small) with respect to thesmaller eigenvalue λ₂ cannot be put into practical use, the entirecommunication channel capacity C_(all) decreases accordingly.

The present invention is aimed at restricting generation of such smalleigenvalues and effectively utilizing the entire communication channelcapacity. In accordance with the present invention, the matrix elementsof the matrix HH*, that is, the matrix elements h_(ij) of thecommunication channel matrix H, are controlled so that the eigenvaluesto be obtained vary only in a very small range. More specifically, theeigenvalues of HH* are first calculated based on the current channelmatrix H, and the average value λ_(ave) of the eigenvalues is thencalculated. The matrix elements h_(ij)′ of such a matrix (H′)(H′)* as toprovide the same eigenvalue as the average value λ_(ave) is inverselycalculated. In other words, the matrix elements h_(ij)′ of a channelmatrix H′ are inversely calculated. The antenna directivity is thencontrolled so that the current channel matrix H approaches the inverselycalculated channel matrix H′. As a result, the eigenvalue variationbecomes narrower in the communication channels based on the updatedchannel matrix. The smallest eigenvalue variation can be obtained whenall the eigenvalues are equal to the average value λ_(ave). If such acommunication environment is realized, the communication channelcapacities can be more efficiently utilized.

In a case where the communication channel capacity with respect to theeigenvalue λ_(ave) is represented by C _(ave), with M and N being 2, theentire communication channel capacity C_(all) is expressed by:C_(all)=2C_(ave)

The communication channel capacity based on the average value λ_(ave) ofthe eigenvalues is represented by the curves MIMO_(average) shown inFIGS. 4 and 5, and the entire capacity is represented by the curvesMIMO_(average total) . In the example shown in FIG. 4, each of the twocommunication channels provides the capacity represented by the curveMIMO_(average). In the example shown in FIG. 5, each of the fourcommunication channels provides the capacity represented by the curveMIMO_(average). The entire communication channel capacity calculated bymultiplying the average-value communication channel capacity by thenumber of ranks is greater than the sum of the communication channelcapacities based on the respective eigenvalues. Furthermore, thecommunication channel capacity (MIMO_(average)) based on the averagevalue provides a more preferable communication path than a SISO system.More specifically, if the matrix elements of the channel matrix H areadjusted so that the eigenvalues of HH* become equal to the averagevalue of the eigenvalues, the probability of the communication channelcapacity with respect to the adjusted matrix becoming smaller than thatof a SISO system is greatly reduced. Furthermore, as shown in FIGS. 6and 7, the bit error rate (the curve MIMO_(average)) of thecommunication channel based on the average value λ_(ave) of theeigenvalues is much lower than the bit error rate (the curveMIMO_(total)) of a case in which the eigenvalues vary greatly.

If the variation of eigenvalues is restricted in the above manner, thevariation of the corresponding communication channel capacities is alsonarrowed, and the bit error rate is lowered. Accordingly, the entirecommunication channel capacity can be efficiently utilized. It should beobvious to those skilled in the art that the above tendency can beobserved not only in cases where M and N are 2 or 4, but also in caseswhere M and N are any other integers.

The following is a description of embodiments of the present invention,with reference to the accompanying drawings.

FIG. 8 illustrates wireless communication apparatuses 802 and 804 thatare employed in a MIMO wireless communication system in accordance withthe present invention. The wireless communication apparatus 802 includesM antenna units 806 that transmit and receive radio frequency signals.Here, M is an integer of 2 or greater. In this embodiment, each antennaof the antenna units 806 is used both for transmission and reception,utilizing a switch for alternative modes or a frequency sharing device(not shown). However, in other embodiments, antenna units may beprovided especially for transmission, while the other antenna units areprovided especially for reception. Also, other elements may accompanythe antenna units. In this embodiment, each of the M antenna units 806is formed by an adaptive array antenna that can control directivity. Inother embodiments, however, some of the M antenna units 806 may beformed by adaptive array antennas, and each of the other antenna units806 may be formed by a feeder antenna. As is described below, matrixelements h_(ij) determine which one(s) of antenna units 806 should be anadaptive array antenna.

The wireless communication apparatus 802 also includes converter units808 corresponding to the M antenna units 806. The converter units 808convert analog signals supplied from the antenna units 806 into digitalsignals for a weight controlling unit (described later), and vice versa.At a time of transmission, each of the converter units 808 functions asa digital-analog converter. At a time of reception, each of theconverter units 808 functions as an analog-digital converter. In a casewhere transmission channels are provided separately from receptionchannels, however, digital-analog converter units may be providedseparately from analog-digital converter units.

The wireless communication apparatus 802 also includes a weightcontrolling unit 810 that controls the weights with respect to the Mantenna units 806. The wireless communication apparatus 802 can allocatea suitable weight μj to each digital signal to be input to converterunits 808 and each digital signal output from the converter units 808.Here, j is an integer between 1 and M.

For ease of explanation, the wireless communication apparatuses 802 and804 of this embodiment have the same structures, and therefore, thewireless communication apparatus 804 is not described in detail. Thewireless communication apparatus 804 includes N antenna units 812 eachconnected to a converter unit 814. Here, N is an integer of 2 orgreater, and is either the same as M or different from M. Each digitalsignal to be input to and output from the converter units 814 is given aweight v_(i) by a weight controlling unit 816. Here, i is an integerbetween 1 and N.

FIG. 9 is a functional block diagram of the weight controlling units 810and 816. Each of the weight controlling units 810 and 816 includes acontroller 902 that controls the operation of each of the followingcomponents: a measuring unit 904 that measures each signal supplied fromthe antenna units; a notifying unit 906 that notifies the other end incommunication of channel matrix information; an eigenvalue calculatingunit 908 that calculates the eigenvalues of a matrix HH*, or the like;an inverse calculation unit 910 that calculates a channel matrix H′after updating; and a weight adjusting unit 912 that controls thedirectivity of the adaptive array antenna. The directivity control maybe performed through beam-forming for steering main beams toward desiredwaves, or through null-steering for steering nulls toward interferers,or through an operation that combines the above two operations. In anyway, the directivity should be adjusted so that thesignal-to-interference-plus-noise ratio increases to the maximum.

The operations are next described. In this embodiment, the wirelesscommunication apparatus 802 is at the reception end, and the wirelesscommunication apparatus 804 is at the transmission end, for ease ofexplanation. However, it is of course possible to switch the sides.First, the wireless communication apparatus 802 performs front-endoperations such as frequency conversion and band limitation on eachradio frequency signal supplied from the antenna units 806. Theconverter units 808 convert analog signals into digital signals, and thedigital signals are suitably weighted. The weighted digital signals arethen introduced into the weight controlling unit 810. It should be notedthat the components used for the front-end operations are not shown inthe drawing. The weight controlling unit 810 measures each receivedsignal, so as to determine the matrix elements h_(ij) of the currentchannel matrix H. Here, i represents an integer between 1 and N, and jrepresents an integer between 1 and M. The matrix element informationobtained through the measurement is then sent to the other end ofcommunication, such as the wireless communication apparatus 804, via awireless channel. The signal processing for the notification isperformed by the notifying unit 906 under the control of the controller902. Through the notification, the wireless communication apparatuses802 and 804 on the transmission and reception ends can share theknowledge with respect to the current channel matrix H. Although themeasuring unit 904 and the notifying unit 906 are not necessarilyrequired in all wireless communication apparatuses, every wirelesscommunication apparatus should at least be capable of utilizing theinformation of the current channel matrix H.

Based on the measured or sent current channel matrix H, the weightcontrolling unit 810 calculates the eigenvalues λ_(i) of the HH* (ibeing an integer between 1 and r, and r representing the number of ranksof the matrix HH*), the total value of the eigenvalues, and the averagevalue λ_(ave) of the eigenvalues. These operations are performed by theeigenvalue calculating unit 908. As the M antenna units 806 and the Nantenna units 812 exist in this embodiment, the channel matrix H is amatrix of M by N, and the matrix HH* is a square matrix of N by N.Accordingly, N eigenvalues λ_(i) are normally obtained (λ₁ □ . . . □λ_(N)).

The weight controlling unit 810 then inversely calculates such a channelmatrix H_(ave) that all the eigenvalues become equal to the averagevalue λ_(ave), using the average value λ_(ave) in the inversecalculation. In other words, the channel matrix H_(ave) is determined sothat all the eigenvalues of a matrix (H_(ave)) (H_(ave))* become equalto the average value λ_(ave). This operation is performed by the inversecalculation unit 910.

The weight controlling unit 810 then controls the adaptive array antennadirectivity of the antenna units 806, so that the current channel matrixH approaches the inversely calculated channel matrix H_(ave). Thisoperation is performed by the weight adjusting unit 912. There arevarious techniques for adjusting the contents of a channel matrix. Forexample, the matrix elements h_(ij) can be made larger in the followingmanner. First, code sequences C₁ through C_(M) that vertically cross oneanother are allocated in advance to the M antenna units 806 of thewireless communication apparatus 802. Likewise, code sequences D₁through D_(N) that vertically cross one another are allocated in advanceto the N antenna units 812 of the wireless communication apparatus 804.These code sequences are known to both the transmission end and thereception end. The jth antenna unit 812 of the wireless communicationapparatus 804 steers the main beams in the incoming direction of thecode sequence C_(j), and the ith antenna unit 806 of the wirelesscommunication apparatus 802 steers the main beams in the incomingdirection of the code sequence D_(i). By doing so at both ends, thematrix elements h_(ij) can be adjusted. Since the code sequencesvertically cross one another, the matrix elements can be distinguishedfrom one another. On the other hand, if nulls are steered, instead ofmain beams, the matrix elements h_(ij) can be made smaller. Thedirectivity control may be performed either independently of or inconjunction with the weights μj and v_(i) given to the antenna units 806and 812.

In this embodiment, all the M antenna units 806 and the N antenna units812 are formed by adaptive array antennas, and the directivity of eachof the antenna units 806 and 812 can be adjusted separately from theothers. Accordingly, all the matrix elements h_(ij) can be adjusted. Inthis aspect, the wireless communication apparatuses 802 and 804 greatlydiffer from a conventional MIMO wireless communication apparatus inwhich antenna units are formed by individual antenna elements, insteadof adaptive array antennas. Also, in a case where a part of the matrixelements h_(ij) is to be adjusted, it is possible to employ an adaptivearray antenna for a part of the antenna units.

In this embodiment, the matrix calculated by the inverse calculationunit 910 has eigenvalues that are all equal to the average valueλ_(ave). As described above, in such a communication environment, theeigenvalues do not vary, all the communication channels have the samecommunication channel capacity C _(ave), and the entire communicationchannel capacity C_(all) can be effectively utilized. In accordance withthe present invention, a great effect can be obtained by narrowing thevariation of the eigenvalues, not to mention by eliminating thevariation of the eigenvalues. As long as an extremely small eigenvalueis not generated, or as long as a communication channel with anextremely poor throughput and an extremely high bit error rate is notgenerated, the entire communication channel capacity C_(all) can be usedin actual communications. Therefore, the inverse calculation unit 910advantageously calculates the matrix H′ so that the eigenvalues of(H′)(H′)* fall within a predetermined range that includes the averagevalue λ_(ave) but does not include the smallest eigenvalue λ_(min). Itis also possible to set such a range that does not include the smallesteigenvalue and the largest eigenvalue but does include the average valueλ_(ave). In either way, the eigenvalue variation of the newly calculatedmatrix (H′)(H′)* should be made narrower than the eigenvalue variationof the current matrix HH*.

The adaptive array antennas that can be employed for the antenna units806 and 812 of this embodiment may be of any type that can feed analogsignals to the converter units 808 and 814, and receive analog signalsfrom the converter units 808 and 814. It is therefore possible to employadaptive array antennas of a spatial composition type or a phased arraytype for the antenna units 806 and 812.

FIG. 10 illustrates an adaptive array antenna 1000 of the spatialcomposition type that can be employed for the antenna units 806 and 812.As shown in FIG. 10, the adaptive array antenna 1000 includes a feederantenna element 1002 that is connected to the converter units 808 and814 shown in FIG. 8, and non-feeder antenna elements 1004. For ease ofexplanation, the components to be used for front-end operations such asfrequency conversion and band limitation are not shown in FIG. 10. Theantenna elements are arranged at a distance shorter than a half-wavelength from one another, so that the spatial correlation among theantenna elements can be great. Each of the non-feeder antenna elements1004 is connected to a ground potential via a variable reactance circuitunit 1006 that can vary the reactance in accordance with controlsignals. Each control signal for the variable reactance circuit unit1006 is adaptively controlled by a variable reactance controllingcircuit unit 1008. This variable reactance controlling circuit unit 1008may be provided in the weight controlling units 810 and 816, or may beprovided independently. Each control signal may be generated inconjunction with the weights μj and v_(i) given to the antenna units 806and 812, or may be generated independently.

With such an adaptive array antenna of the spatial composition type, thenumber of elements to be controlled can be reduced (each one of thevariable reactance circuit units 1006 can be formed by one capacitor,for example). Thus, the matrix elements h_(ij) of a channel matrix canbe readily adjusted.

FIG. 11 illustrates an adaptive array antenna 1100 of the phased arraytype that can be employed for the antenna units 806 and 812. As shown inFIG. 11, the adaptive array antenna 1100 includes feeder antennas 1102,and radio frequency weighting circuit units 1104 that weight signalssupplied from the feeder antennas 1102 in accordance with controlsignals. The radio frequency weighting circuit units 1104 adjust thephase of each signal (in some special cases, the amplitude as well asthe phase of each signal can be adjusted). Each output from the radiofrequency weighting circuit units 1104 is supplied to a radio frequencycompounding circuit unit 1106 that outputs a composite analog signal tothe converter units 808 and 814. The composite analog signal is alsosupplied to a radio frequency weight controlling circuit 1108 thatcontrols weights to be added to the feeder antenna elements. This radiofrequency weight controlling unit 1108 may be provided in the weightcontrolling units 810 and 816 or may be provided independently. Further,each control signal may be generated in conjunction with the weights μjand v_(i) given to the antenna units 806 and 812, or may be generatedindependently.

With such an adaptive array antenna of the phased array type, phases canbe arbitrarily adjusted by the radio frequency weight controllingcircuit units 1104, and accordingly, a greater degree of freedom can beallowed for the adjusting operation. Thus, the matrix elements h_(ij) ofa channel matrix can be minutely adjusted.

FIG. 12 illustrates a case where polarized wave sharing antennas areemployed as antenna elements. In this structure, radio frequencyweighting circuit unit 1206 and 1208 are provided for polarized wavesharing antennas 1202 and 1204, respectively. The radio frequencyweighting circuit units 1206 and 1208 weight signals in accordance withcontrol signals, and supply the weighted signals to a radio frequencycompounding circuit unit 1210 that compounds the weighted signals. Thecomposite signal is then supplied from the radio frequency compoundingcircuit unit 1210 to the converter units 808 and 814 as well as a radiofrequency weight controlling circuit unit 1212 that generates controlsignals.

With such a structure, the channel matrix elements h_(ij) can be moreminutely adjusted, because the polarization characteristics of radiosignals, as well as the amplitudes and phases, can be taken intoconsideration.

As described so far, at least one adaptive array antenna is employed forthe antenna units used in a MIMO wireless communication apparatus ofthis embodiment. The weight controlling unit of the wirelesscommunication apparatus calculates such a channel matrix that narrowsthe eigenvalue variation. The adaptive array antenna directivity is thencontrolled in such a manner that the current channel matrix approachesthe calculated channel matrix. After the eigenvalue variation isnarrowed (ideally, all the eigenvalues become equal to the average valueλ_(ave), and accordingly, the eigenvalue variation is eliminated), thevariation of communication channel capacities corresponding to theeigenvalues is also narrowed. As a result, the communication channelcapacities corresponding to all the eigenvalues can be effectivelyutilized in actual communications.

It should be noted that the present invention is not limited to theembodiments specifically disclosed above, but other variations andmodifications may be made without departing from the scope of thepresent invention.

This patent application is based on Japanese Priority Patent ApplicationNo. 2003-200446, filed on Jul. 23, 2003, the entire contents of whichare hereby incorporated by reference.

1. A wireless communication apparatus that is employed in amultiple-input-multiple-output wireless communication system,comprising: a plurality of antenna units that transmit or receive aradio frequency signal; and a weight controlling unit that gives aweight with respect to each of the plurality of antenna units, whereinat least one of the plurality of antenna units is formed by an adaptivearray antenna unit, and the adaptive array antenna unit comprises aplurality of antenna elements and has a directivity that is changed byvarying weights with respect to the plurality of antenna elements. 2.The wireless communication apparatus as claimed in claim 1 wherein theweight controlling unit comprises: an eigenvalue calculating unit thatcalculates eigenvalues of a matrix represented by the product of acurrent channel matrix representing the transmission characteristics ofwireless transmission channels of the respective antenna units and aconjugate transposed matrix of the current channel matrix; an inversecalculation unit that calculates such a channel matrix as to have alleigenvalues within a predetermined range that includes the average valueof the calculated eigenvalues but does not include the smallest one ofthe calculated eigenvalues; and a directivity adjusting unit thatadjusts the directivity of the adaptive array antenna unit, so that thecurrent channel matrix approaches the channel matrix calculated by theinverse calculation unit.
 3. The wireless communication apparatus asclaimed in claim 1 further comprising a plurality of converter unitsthat are provided for the plurality of antenna units, each converting adigital signal into an analog signal and vise versa, wherein the weightcontrolling unit adds a weight to each signal to be input to or outputfrom the converter units.
 4. The wireless communication apparatus asclaimed in claim 1 wherein each of the antenna units is formed by anadaptive array antenna unit.
 5. The wireless communication apparatus asclaimed in claim 1 wherein the adaptive array antenna unit includes aplurality of feeder antennas that are the antenna elements, and acompounding unit that compounds signals supplied from the feederantennas, and wherein the directivity is adjusted by changing therelative amplitude or phase of each of the radio frequency signals withrespect to the feeder antennas.
 6. The wireless communication apparatusas claimed in claim 1 wherein the antenna elements of the adaptive arrayantenna unit include a feeder antenna and a plurality of non-feederantennas, and the directivity is adjusted by changing a variablereactance value that is given to each of the non-feeder antennas.
 7. Thewireless communication apparatus as claimed in claim 1 wherein theantenna elements of the adaptive array antenna unit are polarized wavesharing antennas.
 8. The wireless communication apparatus as claimed inclaim 1 wherein the weight controlling unit adaptively controls thedirectivity so as to steer a main lobe toward a desired signal.
 9. Thewireless communication apparatus as claimed in claim 1 wherein theweight controlling unit adaptively controls the directivity so as tosteer a null toward an interferer.
 10. The wireless communicationapparatus as claimed in claim 1 further comprising a channel matrixcalculating unit that measures one of the received radio frequencysignals so as to calculate the current channel matrix.
 11. The wirelesscommunication apparatus as claimed in claim 10 wherein the channelmatrix calculating unit utilizes code sequences that are allocated inadvance to the antenna units, so as to distinguish matrix elements ofthe channel matrix from one another, the code sequences verticallycrossing one another.
 12. The wireless communication apparatus asclaimed in claim 2 wherein the predetermined range does not include thelargest value and the smallest value among the calculated eigenvalues.13. The wireless communication apparatus as claimed in claim 2 whereinthe inverse calculation unit calculates such a channel matrix that alleigenvalues become equal to the average value.
 14. Amultiple-input-multiple-output wireless communication system comprisinga wireless transmission apparatus and a wireless reception apparatus, atleast one of the wireless transmission apparatus and the wirelessreception apparatus comprising: a plurality of antenna units thattransmit or receive a radio frequency signal; and a weight controllingunit that gives a weight with respect to each of the plurality ofantenna units, wherein at least one of the plurality of antenna units isformed by an adaptive array antenna unit, and the adaptive array antennaunit comprises a plurality of antenna elements and has a directivitythat is changed by varying weights with respect to the plurality ofantenna elements.
 15. The multiple-input-multiple-output wirelesscommunication system as claimed in claim 14 wherein the current channelmatrix is known to both the wireless transmission apparatus and thewireless reception apparatus.
 16. The multiple-input-multiple-outputwireless communication system as claimed in claim 14 wherein thewireless transmission apparatus is notified of the current channelmatrix determined in the wireless reception apparatus.